In developing effective strategies to control diseases caused by pathogenic viruses, the ability to manipulate DNA replication in their genomes provide possible ways to alter viral growth. Replication origins in DNA are considered major sites for regulating genome replication. With the accumulation of DNA sequence data in vast computer databases readily accessible via the Internet, computer based sequence analysis tools can be developed to help locate replication origins in viral genomes It has been observed in many studies that clusters of close repeats and inversions are characteristic patterns found in the nucleotide sequences at the replication origins in a number of double stranded (ds)DNA viruses. This four year project is designed to formulate a computational method for predicting the locations of replication origins in viral genomes. Specifically, probabilistic models for the occurrences of close repeats and inversions in viral DNA genomes will first be developed. The scan statistic theory, which is a powerful generalized likelihood ratio test will be investigated to derive a rigorous criterion to identify unusual clustering of close repeats and inversions. The theoretical results obtained will be used to establish a computational algorithm for locating significant clusters of repeats and inversions on families of viral genomes. The algorithm will be implemented as a web-accessible package of computer programs. These programs will be used to predict the locations of replication origins in complete viral genome sequences deposited in GenBank. The predictions will be tested against all known replication origins in the test genomes to optimize the parameters of the algorithm to achieve the highest degree of prediction accuracy. Upon completion of this project, the PI expects to be able to generalize the mathematical models, and adapt the computational algorithms to analyze bacterial and eukaryotic genomes. The knowledge gathered from characteristics of replication origins in a broad spectrum of genome sequences will contribute to the elucidation of the detailed mechanisms of DNA replication.